statistics

问题 I would like to compare different binary classifiers in Python. For that, I want to calculate the ROC AUC scores, measure the 95% confidence interval (CI) , and p-value to access statistical significance. Below is a minimal example in scikit-learn which trains three different models on a binary classification dataset, plots the ROC curves and calculates the AUC scores. Here are my specific questions: How to calculate the 95% confidence interval (CI) of the ROC AUC scores on the test set? (e.g

问题 Closed. This question is not reproducible or was caused by typos. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed last month . Improve this question I've been trying to run this code: lm_model <- lm(Calories ~ Sodium + Carbohydrates + Protein + Caffeine + Dietary Fiber, data = Starbucks) but I keep getting Error: unexpected symbol in "lm_model <- lm(Calories ~ Sodium + Carbohydrates + Protein + Caffeine +

问题 I'm trying to make a martingale simulation in R where I bet an amount and if I win I bet the same amount but if I lose, I bet double the amount. I do this until I run out of money to bet or have bet 100 times. I then have to do the martingale simulation 100 times. When I apply my code, I get the following errors; Error: unexpected '}' in "}" (I think all brackets are accounted for) Error in martingale_function(m, c, n, p) : could not find function "martingale_function" (I don't know why I get

问题 I'm trying to make a martingale simulation in R where I bet an amount and if I win I bet the same amount but if I lose, I bet double the amount. I do this until I run out of money to bet or have bet 100 times. I then have to do the martingale simulation 100 times. When I apply my code, I get the following errors; Error: unexpected '}' in "}" (I think all brackets are accounted for) Error in martingale_function(m, c, n, p) : could not find function "martingale_function" (I don't know why I get

问题 I am trying to get the F-statistic and p-value for each of the covariates in GLM. In Python I am using the stats mode.formula.api to conduct the GLM. formula = 'PropNo_Pred ~ Geography + log10BMI + Cat_OpCavity + CatLes_neles + CatRural_urban + \ CatPred_Control + CatNative_Intro + Midpoint_of_study' mod1 = smf.glm(formula=formula, data=A2, family=sm.families.Binomial()).fit() mod1.summary() After that I am trying to do the ANOVA test for this model using the anova in statsmodels.stats table1

问题 I am trying to get the F-statistic and p-value for each of the covariates in GLM. In Python I am using the stats mode.formula.api to conduct the GLM. formula = 'PropNo_Pred ~ Geography + log10BMI + Cat_OpCavity + CatLes_neles + CatRural_urban + \ CatPred_Control + CatNative_Intro + Midpoint_of_study' mod1 = smf.glm(formula=formula, data=A2, family=sm.families.Binomial()).fit() mod1.summary() After that I am trying to do the ANOVA test for this model using the anova in statsmodels.stats table1

问题 I am trying to get the F-statistic and p-value for each of the covariates in GLM. In Python I am using the stats mode.formula.api to conduct the GLM. formula = 'PropNo_Pred ~ Geography + log10BMI + Cat_OpCavity + CatLes_neles + CatRural_urban + \ CatPred_Control + CatNative_Intro + Midpoint_of_study' mod1 = smf.glm(formula=formula, data=A2, family=sm.families.Binomial()).fit() mod1.summary() After that I am trying to do the ANOVA test for this model using the anova in statsmodels.stats table1

问题 I am trying to find an optimal distribution curve fit to my data consisting of y-axis = [0, 0, 0, 0, 0.24, 0.53, 0.49, 0.64, 0.54, 0.78, 0.59, 0.44, 0.34, 0.88, 0.2, 0.49, 0.39, 0.39, 0.29, 0.2, 0.05, 0.05, 0.25, 0.05, 0.1, 0.15, 0.1, 0.1, 0.1, 0, 0, 0, 0, 0] y-axis are probabilities of an event occurring in x-axis time bins: x-axis = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0,

问题 I want to create a list for my classroom of every possible group of 4 students. If I have 20 students, how I can I create this, by group, in R where my rows are each combination and there are 20 columns for the full list of student ids and columns 1-4 are "group1", 5-9 are "group2" etc. etc. The below gives a list of possible combinations for each single group of 4 students (x1, x2, x3, and x4). Now, for each row listed, what are the possibilities for the other 4 groups of 4 students? So,

问题 I want to create a list for my classroom of every possible group of 4 students. If I have 20 students, how I can I create this, by group, in R where my rows are each combination and there are 20 columns for the full list of student ids and columns 1-4 are "group1", 5-9 are "group2" etc. etc. The below gives a list of possible combinations for each single group of 4 students (x1, x2, x3, and x4). Now, for each row listed, what are the possibilities for the other 4 groups of 4 students? So,